Building a vertically integrated genomic learning health system: The biobank at the Colorado Center for Personalized Medicine.

Precision medicine initiatives across the globe have led to a revolution of repositories linking large-scale genomic data with electronic health records, enabling genomic analyses across the entire phenome. Many of these initiatives focus solely on research insights, leading to limited direct benefit to patients. We describe the biobank at the Colorado Center for Personalized Medicine (CCPM Biobank) that was jointly developed by the University of Colorado Anschutz Medical Campus and UCHealth to serve as a unique, dual-purpose research and clinical resource accelerating personalized medicine. This living resource currently has more than 200,000 participants with ongoing recruitment. We highlight the clinical, laboratory, regulatory, and HIPAA-compliant informatics infrastructure along with our stakeholder engagement, consent, recontact, and participant engagement strategies. We characterize aspects of genetic and geographic diversity unique to the Rocky Mountain region, the primary catchment area for CCPM Biobank participants. We leverage linked health and demographic information of the CCPM Biobank participant population to demonstrate the utility of the CCPM Biobank to replicate complex trait associations in the first 33,674 genotyped individuals across multiple disease domains. Finally, we describe our current efforts toward return of clinical genetic test results, including high-impact pathogenic variants and pharmacogenetic information, and our broader goals as the CCPM Biobank continues to grow. Bringing clinical and research interests together fosters unique clinical and translational questions that can be addressed from the large EHR-linked CCPM Biobank resource within a HIPAA- and CLIA-certified environment.

Identifying factors and causal chains associated with optimal implementation of Lynch syndrome tumor screening: An application of coincidence analysis.

PURPOSE: This study compared Lynch syndrome universal tumor screening (UTS) across multiple health systems (some of which had 2 or more distinct UTS programs) to understand multilevel factors that may affect the successful implementation of complex programs. METHODS: Data from 66 stakeholder interviews were used to conduct multivalue coincidence analysis and identify key factors that consistently make a difference in whether UTS programs were implemented and optimized at the system level. RESULTS: The selected coincidence analysis model revealed combinations of conditions that distinguish 4 optimized UTS programs, 10 nonoptimized programs, and 4 systems with no program. Fully optimized UTS programs had both a maintenance champion and a positive inner setting. Two independent paths were unique to nonoptimized programs: (1) positive attitudes and a mixed inner setting or (2) limited planning and engaging among stakeholders. Negative views about UTS evidence or lack of knowledge about UTS led to a lack of planning and engaging, which subsequently prevented program implementation. CONCLUSION: The model improved our understanding of program implementation in health care systems and informed the creation of a toolkit to guide UTS implementation, optimization, and changes. Our findings and toolkit may serve as a use case to increase the successful implementation of other complex precision health programs.

Primary care providers' preferences for the communication and management of actionable genomic findings from a research biobank.

Purpose: Little is known about non-genetics health care specialists' attitudes toward the return and utilization of actionable genomic results from a research biobank. We surveyed primary care providers (PCPs) to explore their perspectives on these results and their preferences for return. Methods: We administered a paper and web-based 27-question survey to PCPs residing locally and caring for adult patients. Recruitment was conducted in person and by email, focusing on PCPs likely to interact with results generated by our institution's biobank. Results: Of the ~482 PCPs contacted, 77 (16%) returned surveys. Although most respondents (90%) prefer that a genetics specialist be involved in communicating biobank-generated genomic results to patients, about 40% of respondents reported that a PCP shares the responsibility to discuss these results along with other specialists. A majority of respondents (74%) felt uncomfortable communicating these results to patients. However, respondents reported significantly greater comfort with this process when offered targeted educational resources (62% with vs 10% without resources; P < 10-5). Conclusion: PCPs recognize the need to engage with their patients' biobank-generated genomic results but feel uncomfortable in doing so. Relevant resources are needed to improve PCPs' confidence in the use of these types of results to affect patient care.